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@TsinghuaC3I

TsinghuaC3I

Center for Collaborative & Conversational Intelligence at Tsinghua University

The Center for Collaborative & Conversational Intelligence (C3I) is affiliated with the Department of Electronic Engineering at Tsinghua University and is led by Professor Bowen Zhou.

Our research objectives are as follows:

  1. Specialization and Alignment of Foundation Models: This involves in-depth research on the architecture design, training, and alignment of foundation models, exploring specialization in reasoning.
  2. Multi-Dimensional Collaborative Research: Based on a cognitive collaboration framework incorporating both System 1 and System 2, this area explores collaboration between large and small models, multimodal collaboration, and human-machine collaboration. It also investigates the interpretable mechanisms of neurodynamics and theories of sustainable hybrid human-machine intelligence.
  3. Application Development for Scientific Discovery: Focused on the biomedical field, this research utilizes collaborative interaction technologies to drive knowledge innovation and promote scientific discoveries and technological advancements.

Popular repositories Loading

  1. SoRA SoRA Public

    The source code of the EMNLP 2023 main conference paper: Sparse Low-rank Adaptation of Pre-trained Language Models.

    Python 57 8

  2. UltraMedical UltraMedical Public

    UltraMedical: Building Specialized Generalists in Biomedicine

    41

  3. Intuitive-Fine-Tuning Intuitive-Fine-Tuning Public

    Intuitive Fine-Tuning: Towards Simplifying Alignment into a Single Process

    8

  4. FS-GEN FS-GEN Public

    Fast and Slow Generating: An Empirical Study on Large and Small Language Models Collaborative Decoding. https://arxiv.org/abs/2406.12295

    Python 6

  5. CRaSh CRaSh Public

    The source code of the EMNLP 2023 main conference paper: "CRaSh: Clustering, Removing, and Sharing Enhance Fine-tuning without Full Large Language Model."

    5

  6. LLM4BioHypoGen LLM4BioHypoGen Public

    Accepted to COLM 2024, "Large Language Models as Biomedical Hypothesis Generators: A Comprehensive Evaluation"

    Python 2

Repositories

Showing 8 of 8 repositories
  • LLM4BioHypoGen Public

    Accepted to COLM 2024, "Large Language Models as Biomedical Hypothesis Generators: A Comprehensive Evaluation"

    TsinghuaC3I/LLM4BioHypoGen’s past year of commit activity
    Python 2 0 0 0 Updated Jul 15, 2024
  • UltraMedical Public

    UltraMedical: Building Specialized Generalists in Biomedicine

    TsinghuaC3I/UltraMedical’s past year of commit activity
    41 0 0 0 Updated Jul 12, 2024
  • FS-GEN Public

    Fast and Slow Generating: An Empirical Study on Large and Small Language Models Collaborative Decoding. https://arxiv.org/abs/2406.12295

    TsinghuaC3I/FS-GEN’s past year of commit activity
    Python 6 0 0 0 Updated Jun 19, 2024
  • Intuitive-Fine-Tuning Public

    Intuitive Fine-Tuning: Towards Simplifying Alignment into a Single Process

    TsinghuaC3I/Intuitive-Fine-Tuning’s past year of commit activity
    8 0 2 0 Updated Jun 4, 2024
  • CoGenesis Public

    CoGenesis: A Framework Collaborating Large and Small Language Models for Secure Context-Aware Instruction Following. ACL@2024 Main

    TsinghuaC3I/CoGenesis’s past year of commit activity
    0 0 0 0 Updated Jun 1, 2024
  • .github Public
    TsinghuaC3I/.github’s past year of commit activity
    0 0 0 0 Updated Apr 27, 2024
  • SoRA Public

    The source code of the EMNLP 2023 main conference paper: Sparse Low-rank Adaptation of Pre-trained Language Models.

    TsinghuaC3I/SoRA’s past year of commit activity
    Python 57 8 6 0 Updated Mar 5, 2024
  • CRaSh Public

    The source code of the EMNLP 2023 main conference paper: "CRaSh: Clustering, Removing, and Sharing Enhance Fine-tuning without Full Large Language Model."

    TsinghuaC3I/CRaSh’s past year of commit activity
    5 0 1 0 Updated Oct 17, 2023

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